5 results about "Sample tracking" patented technology

Systems and methods for tracking samples via sample tracking chains are presented. Sample tracking chains represent digital data structures instantiated according to intrinsic properties of a sample. Each link in the chain is a block of data representing an observed intrinsic state of the sample and is linked at least to a previous block representing a previous state. The sample tracking chain and blocks can be indexed for later retrieval by the intrinsic properties of the corresponding sample's state. The sample tracking chain can take the form of a blockchain possibly stored as part of a private or public distributed ledger. Disclosed sample tracking chains provide a full life cycle audit trail for sample processing.

This application provides a method and system for batch progress monitoring of animal disease testing samples, belonging to the field of intelligent monitoring technology. The method includes: introducing an online mirroring system to receive testing tasks and perform lightweight simulations to determine the testing chain, based on the testing process cycle; verifying and correcting based on personnel and equipment status; receiving test samples and assigning batch radio frequency coding (RFID) identification; and implementing batch-driven testing management and data storage on the testing chain through collaborative RFID tracking and visual monitoring to determine the testing data chain and establish a knowledge graph of testing through batch mining. This application solves the technical problem in existing technologies where isolated information and discontinuous data at each stage of the testing process make it difficult to monitor and track sample batch progress in real time, thus affecting testing efficiency. By introducing an online mirroring system combined with RFID identification for full-process sample tracking, the efficiency of disease testing is improved.

The application discloses a quality control and sample tracking management method for a whole process of gene detection, and relates to the field of sample tracking management. First, the reagent flow parameter is converted into a digital activity vector by using the attenuation integral technology. Then, a collaborative feature matrix coupled across dimensions is constructed by fusing the features of the activity vector and the library quality control data. On this basis, the calibration instruction set executable by the device is reversely solved based on the precision loss gradient and combined with the hardware parameter mapping table, so that the sequencer can automatically adjust the underlying operation parameters according to the real-time performance of the reagent. Finally, the quality control tracking report is generated through the whole-link correlation audit, the whole-process transparency control from the underlying biochemical fluctuation to the macro quality state is realized, and the sequencing deviation caused by the dynamic biochemical attenuation is fundamentally eliminated.

Disclosed herein are scientific instrument support systems, as well as related methods, computing devices, and computer-readable media. For example, in some embodiments, samples are tracked using unique identifiers. An autosampler may detect the samples using unique identifiers and provide alerts when the sample is placed in the wrong location or when an incorrect or incompatible workflow is selected for the sample.

A system and method are described for identifying the location of jamming or spoofing of information that is used in a Global Navigation Satellite System (GNSS) geolocation system, in areas in which it is difficult or impractical to install detection devices. The system and method make use of existing vessel-tracking technologies, such as Automatic Dependent Surveillance– Broadcast (ADS-B) – for aircraft vessels – and Automatic Identification System (AIS) – for naval vessels, to collect data on the speed and trajectory of large numbers of vessels and to use that data to extrapolate areas in which spoofing or jamming may be occurring. The system and method include techniques for sampling tracking data over periods of time in order to establish when data is sufficiently anomalous to indicate the potential for spoofing or jamming to be occurring for a particular tracked vessel. The overall system and method also includes a weighting protocol for data from multiple vessels to predict areas in which spoofing or jamming may be occurring by assigning anomalous vessel signals that are geographically nearby to values as to their potential to indicate spoofing or jamming, and thus calculating an area around those vessels as potentially subject to spoofing or jamming. A processing hub or multiple processing hubs include facilities to compare location information received by a group of vessels with anomalous signals and to determine whether the location information for those vessels is consistent with predicted location information for those vessels. In the event that there is a discrepancy between the predicted location information and the received location information, the processing hub or hubs can take a number of remediative actions, such as assigning the calculated area as one that has been identified as being subject to spoofing or jamming, and sending a warning signal to vessels in that calculated area that their GNSS location information may not be reliable. The system and method of the present invention can also alert affected vessels of the need to switch to a backup or alternative geolocation or navigation system, when it is determined that the GNSS geolocation system is determined to be inaccurate or unavailable in an area in which the vessels are currently located. Artificial Intelligence (AI) or Machine Learning (ML) can be used to better predict and correlate data so the most accurate approximation of where spoofing or jamming is occurs may be identified and subscribers to the system may be alerted.